title: HistoStitcher(©): an interactive program for accurate and rapid reconstruction of digitized whole histological sections from tissue fragments.
abstract: We present an interactive program called HistoStitcher(©) for accurate and rapid reassembly of histology fragments into a pseudo-whole digitized histological section. HistoStitcher(©) provides both an intuitive graphical interface to assist the operator in performing the stitch of adjacent histology fragments by selecting pairs of anatomical landmarks, and a set of computational routines for determining and applying an optimal linear transformation to generate the stitched image. Reconstruction of whole histological sections from images of slides containing smaller fragments is required in applications where preparation of whole sections of large tissue specimens is not feasible or efficient, and such whole mounts are required to facilitate (a) disease annotation and (b) image registration with radiological images. Unlike manual reassembly of image fragments in a general purpose image editing program (such as Photoshop), HistoStitcher(©) provides memory efficient operation on high resolution digitized histology images and a highly flexible stitching process capable of producing more accurate results in less time. Further, by parameterizing the series of transformations determined by the stitching process, the stitching parameters can be saved, loaded at a later time, refined, or reapplied to multi-resolution scans, or quickly transmitted to another site. In this paper, we describe in detail the design of HistoStitcher(©) and the mathematical routines used for calculating the optimal image transformation, and demonstrate its operation for stitching high resolution histology quadrants of a prostate specimen to form a digitally reassembled whole histology section, for 8 different patient studies. To evaluate stitching quality, a 6 point scoring scheme, which assesses the alignment and continuity of anatomical structures important for disease annotation, is employed by three independent expert pathologists. For 6 studies compared with this scheme, reconstructed sections generated via HistoStitcher(©) scored higher than reconstructions generated by an expert pathologist using Photoshop.
authors.affiliation: Rutgers University, Department of Biomedical Engineering, Piscataway, NJ 08854, USA.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Chappelow
authors.forename: John E
authors.initials: JE
authors.lastname: Tomaszewski
authors.forename: Michael
authors.initials: M
authors.lastname: Feldman
authors.forename: Natalie
authors.initials: N
authors.lastname: Shih
authors.forename: Anant
authors.initials: A
authors.lastname: Madabhushi
mesh_terms: D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000592:standards*; D008297:Male; D010338:Pathology, Clinical; D010363:Pattern Recognition, Automated / Q000592:standards*; D011471:Prostatic Neoplasms / Q000473:pathology; D012985:Software Design; D014584:User-Computer Interface